{"id":"W3207406191","doi":"10.1109/access.2021.3120419","title":"Automatic Modulation Classification: A Deep Architecture Survey","year":2021,"lang":"en","type":"article","venue":"IEEE Access","topic":"Wireless Signal Modulation Classification","field":"Computer Science","cited_by":157,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"National Research Foundation of Korea","keywords":"Computer science; Deep learning; Convolutional neural network; Modulation (music); Artificial intelligence; Wireless; Signal processing; Artificial neural network; Machine learning; Pattern recognition (psychology); Telecommunications","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000389854,0.0001605733,0.000178925,0.0001487847,0.0001741756,0.0006815977,0.001109906,0.000106013,0.00008435653],"category_scores_gemma":[0.0002052019,0.0001645895,0.00006083085,0.001334822,0.00003592494,0.001171867,0.0001357001,0.0001595663,0.0001088919],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009815427,"about_ca_system_score_gemma":0.0001767653,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003576768,"about_ca_topic_score_gemma":0.0001990957,"domain_scores_codex":[0.9979221,0.0003953145,0.000385384,0.0005858666,0.0004769617,0.0002344207],"domain_scores_gemma":[0.9978439,0.0003165178,0.0002247346,0.001037732,0.0004729882,0.000104103],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001264178,0.0003739448,0.04719737,0.0001198088,0.00008174447,0.00003729491,0.001052316,0.06281608,0.03806282,0.0430177,0.001856261,0.805372],"study_design_scores_gemma":[0.0001157101,0.000004870824,0.4653176,0.00001042825,0.000002690555,0.00001076656,0.000003290606,0.5263922,0.003178188,0.00471593,0.0001269587,0.000121356],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1708924,0.00004100777,0.8257689,0.001664229,0.0005836607,0.0001551799,0.000003637546,0.0002959989,0.0005949884],"genre_scores_gemma":[0.9846735,0.000004968677,0.01461347,0.0003262973,0.000125747,0.00004838791,0.00006770895,0.00001593844,0.0001240047],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8137811,"threshold_uncertainty_score":0.6711763,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08085182175646803,"score_gpt":0.3209410406793151,"score_spread":0.2400892189228471,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}